danmcquillan.org

Abstract for 'Teaching Anti-Fascism Today'

2026-05-07T00:00:00+01:00

My abstract for the workshop on 'Teaching Anti-Fascism Today: Developing and Shaping Practices' to be held at the Institute of Languages, Cultures and Societies, School of Advanced Study, University of London.

An anti-fascist teaching practice is also anti-AI.

The intervention I propose is first and foremost aimed at participants in the workshop. It will argue that AI is a vector for fascistic currents in education and society, and that an anti-fascist teaching practice means resisting AI both as a pedagogic tool and more broadly. The presentation will emphasise that AI is fascistic not only because of the fusion between MAGA and Silicon Valley accelerationism, but due to AI's core operations and infrastructural dependencies. Moreover, AI is being mobilised as a direct attack on teaching and education as such, with the net effect of eliminating spaces of critical thought. Where AI comes to predominate, inside education or in society, it extends a technologically-mediated metapolitics that is fundamentally misogynist and eugenicist.

Spaces of teaching and learning are fundamental to nurturing anti-fascist subjectivities through habits of relational and collective thinking. It's vital that this isn't outmaneuvered by modes of microfascism that are made opaque by manifesting as advanced technologies. The presentation will propose approaches to anti-fascist teaching practice that resist AI's legitimation of fascistic tendencies.

Speaker notes from Resisting Big Tech Empires

2026-04-25T00:00:00+01:00

My speaker notes from the 'Resisting Big Tech Empires' conference, Sat 25th April 2026.

The opening plenary (pictured) was with Anita Gurumurthy of IT for Change and Nick Dearden of Global Justice Now. The afternoon panel was with investigative journalist Nafeez Ahmed.

Opening plenary Q1: "What do we mean when we talk about Big Tech Empires?"

I'm not sure there are Big Tech empires, but there are definitely Big Tech corporations in the middle of a world system collapse. The so-called rules-based order was always a cover story, but now it's over anyway. Power is shifting; it's an interregnum, a time between, and AI is a morbid symptom of it.

By AI, I specifically mean anything built on neural networks, which includes transformer models like ChatGPT. It's important to realise AI isn't a powerful technology, at least not in the sense that's claimed for it. All it can do is correlations; there's no causation, no physics model - just pattern-finding, and now pattern-generation. It's also very reductive and abstracting, and not really able to deal with the context or complexity of the world. As a technology, it's hugely complex but very flaky. However, it is the point of convergence for a number of powerful forces who all see it as a way to hold onto power under rapidly changing conditions.

AI definitely has empire-like aspects, especially its need for continuous growth and expansion, which the industry calls 'scaling'. This is the push from millions to billions to trillions of parameters; a version of so-called growth which, just like GDP, is essentially sociopathic. The accelerating growth is materially visible in the way data centres suck up electricity and water, and the way chip manufacture demands control over mineral supply chains. Another major overlap with empire is eugenics. The 'I' in AI, or the concept of intelligence, comes straight from Galton and Pearson, who justified the British Empire via biology. The computations of AI repeat this kind of stratification and segregation.

While Big Tech may not be an empire in itself, the AI corporates have some characteristics that are very reminiscent of the East India Company; they're very ideological, they're very interventionist, and they're increasingly wedded to military adventurism. Unfortunately, the aspect of AI which sabotages its usefulness in social settings, which is its innate tendency to generate collateral damage through out-of-distribution errors and so-called hallucinations, ceases to be a problem in conflicts where maximum indiscriminate damage is the actual point.

I think it's equally important to focus on energy. It's been so striking to me to see the boasts about AI rendered not as computation, or floating-point operations, but as energy use in gigawatts. This is the imperial pattern; expansion driven by Promethean tech and by burning as much energy as possible. It looks to me a lot like Total Mobilisation, a term coined by ultra-nationalist Ernst Junger to describe the channelling of the entire material and energy resources of a nation into a new technological order; "the conversion of life itself into energy" as nations are "driven relentlessly to seize matter, movement and force through the formalism of technoscience". Total mobilisation legitimates a new form of political order based on the vitalism of conflict.

Whether or not that's what's happening, AI itself is an engine of precaritisation and necropolitics, that form of power which not only discriminates in allocating support for life but sanctions the operations that organise neglect and increase vulnerability to death. Its direction of travel is defining who is more disposable. This doesn't make it Skynet; it's not sci-fi but a direct extension of structural forces, especially racism, misogyny and anthropocentrism.

AI is useless for social reproduction, because a shoddy simulation is no substitute for real care. You can't make worker-friendly AI; it's anti-worker from top-to-bottom. You can't make planet-friendly AI; it burns resources and produces bullshit. The whole AI assemblage is Epstein tech; not simply because the guy himself was involved in it, but because the apparatus of AI is a concentrated network of masculine power which enables abuse at scale. AI is textbook accelerationism, a belief that we should go further and faster, that our tech should be overclocked to the point of meltdown in order to break through the barriers between us and a new era.

The good news is AI isn't inevitable, but there's no going back to a pre-AI age, because AI is an amplifier for the problems we already had. It encourages thoughtlessness in decisions and in expression, and it forces an exclusionary normativity. What it shows us is the wider nihilistic solutionism of those who can't bear to give up one inch of power. AI is a mask-off tech for a very mask-off time; it's a technological reminder that, in the eyes of the powerful, the rest of us are expendable.

Anywhere AI is proposed as a solution, there are already deep problems that need fixing in a different way, usually by more people doing people-stuff; doctors, nurses, teachers and care workers. But we also need to question the ideologies that underpin AI, like productivism and efficiency, and of course the continuation of colonialism which makes any of this possible.

There's a widespread compulsion to preface any criticism of AI by saying 'of course it has great potential for XYZ'; it mostly doesn't, and we just need to stop defending it. Every day we make excuses for AI is another day of real material harms; another day when real problems are hidden behind a smokescreen of high tech, and another day when we're sleepwalking into a much more fascist world.

Opening plenary Q2: "What should our strategies be for resisting these big tech empires?"

Collective refusal can start anywhere, like in school or university for example, with the rejection of technological offloading that research shows makes us less critical. It can start at work, where more people are being forced to use AI, like it or not. Unfortunately, most trade unions seem to have drunk the AI kool aid. Being against AI is a growing social movement that isn't yet conscious of itself.

The fact that so many people are starting to hate AI brings its own risks. When we're pushing back, we need to be careful who we're standing with. We need to be wary of doomers, who believe the risk of AI is superintelligence that will kill us all; that delusion that has more in common with Silicon Valley oligarchs than with the rest of us.

We also need to be wary of policy-types talking about AI sovereignty because that's just nationalism and populism, stoked by domestic elites who are panicking about their place in the new world order. As if scattering flag-flying data centres across the homeland will make AI less harmful! The only kind of sovereignty AI delivers is the one Nazi jurist Carl Schmitt defined as the power to declare the state of exception.

AI has shown us that if we care about justice then we need to pay attention to technopolitics. I'm suggesting we start with a technopolitics of decomputing which, as a simple rule of thumb, is something like; people first, computing last, AI never.

Resisting hyperscale data centres is a great start, as their grid-stressing and water-wasting is a form of low-intensity conflict against local communities. However, stopping the enclosure of electricity and water also raises wider questions, like who controls vital common good resources and how do we re-socialise them? It's an opening for what we could call technopoliticisation, where we see that datacentres also drive overlapping social harms, like algorithmic exploitation in Amazon warehouses, gig work and outsourced data labour, as well as AI-powered targeting for welfare sanctions, deportations and weapons systems.

Like all capitalist technology, the core of AI is expansion and growth. Decomputing is a technopolitics of degrowth, which isn't about all-round austerity but removing the drive for infinite expansion. We need to stop fuelling empire and break its circuits of necropolitical value creation. Decomputing is about deautomatisation; about extracting ourselves from the patterns of machinic relations which are amplified by tech. It's about mutual aid that comes from the recognition of mutual vulnerability, and care that doesn't depend on classifying people according to algorithmic boundaries. Decomputing adopts the approach to tech development outlined in Illich's tools for conviviality; developing tools that enable autonomy and adaptation, rather than the conditioned responses demanded by manipulative systems.

Decomputing means the prefigurative resistance of workers and peoples councils, where directly democracy is a counter to automatisation and collective struggle under conditions of consensus transforms inherited social patterns. Intersecting layers of horizontal governance at local, regional and even international level are not only conceivable but considerably less complex than the tech we’re supposed to bet our future on.

Decomputing is a prioritisation of the periphery and the pluriverse when it comes to visions of future technologies. The aim of decomputing is to deactivate existing computational power, and to return to common use the technical means for making our own arrangements and for infrastructuring the common good.

Afternoon panel: "Is this Technofascism? Rethinking the far right in the age of AI"

[note: on the day I skipped the quote from the ICE resistance organiser for reasons of time, but I've kept it here]

Talking about technofascism means taking both the political and the technological seriously; seeing them as distinct but inseparable, and as co-emergent. I'm going to start on the other side of this binary from Nafeez's talk, i.e. with the tech, to try to explain why AI as a technology is closely wedded to fascistic solutionism.

I think this is important, even if your main concern is fascism not AI, because fascism doesn't return as a tick list of characteristics. Fascism is a fluid and dynamic force which operates at the level of social desires before it appears as jackboots. We need to learn to sense it in our infrastructures as well as in our political discourse.

It's important to remember that contemporary AI isn't just generative but also predictive. The core computational mechanism of all this AI is correlation not causation, which means it's already a form of computational conspiracy theory with no grasp of structural causes. As these systems become pervasive they start to tip the balance of different decisions, producing algorithmic states of exception; forms of exclusion that render people vulnerable in an absolute sense.

Such an apparatus is attractive to the state and corporations, not despite its inability to address structural questions, but because of it.

It's not only that eugenics never went away in dreams of Pioneer Fund recipients, it never went away in our systems of welfare and disability, which became shockingly clear during Covid when 'pre-existing medical condition' became a soothing proxy for disposable. What we arrive at with the merger of opaque AI and existing bureaucracy is what Hannah Arendt called thoughtlessness; the inability to critique instructions, the lack of reﬂection on consequences, and a commitment to the belief that the correct ordering is being carried out.

People expected great things from the EU's AI regulation while forgetting that's the same entity intent on drowning as many refugees in the Mediterranean as possible. AI has become another cog in the already existing machinery for shifting societies towards authoritarianism. By filtering and classifying out-groups as the cause of shoddy services while obscuring structural forces that are actually to blame, it becomes the technological piston in the self-reinforcing cycle created when governments adopt the rhetoric of the far right.

The carelessness at the core of AI makes it useless for social reproduction but very attractive to those who want machinery for mass deportation. The patriotic rhetoric about the UK as an AI superpower is not only nonsense but legitimises the systemic build-out of repressive infrastructure ready for Reform UK to deliver on their minimum demand of 600,000 deportations.

It's right and just to point to the environmental harms of data centres, but we should realise that the real energy source powering AI isn't methane-polluting gas turbines or even the fantasies about nuclear fusion, but fear. The techno-patriarchy everywhere fears the loss of unquestioned mastery. Better to accelerate the burn than admit fragility or allow the rest of us to have a real say in the conditions of our own existence.

So I think the important question isn't so much 'is this technofascism?', but 'what does anti-fascism look like under technopolitical conditions?'.

One thing that both fascism and AI have in common is their need to convince us of their inevitability, which is a giveaway that they're still vulnerable. AI is actually a very shaky system; it's materially unsustainable and floating on a financial bubble. What we need is an alternative technopolitics that enacts what Ivan Illich called counterfoil research: "providing guidelines for detecting the incipient stages of murderous logic in a tool" and "devising tool-systems that optimize the balance of life, thereby maximizing liberty for all".

We don't need to keep a human in the loop, we need to get AI out of the loop altogether, because the whole point of AI is to remove the frictions of individual conscience and collective refusal. Musk's efforts with DOGE are a warning here; it turns out that having centralized, bureaucratized and digitized institutions makes them vulnerable to a cyberattack from within by technofascist nerds. We need more sociocratic patterns, with circular feedback loops up and down the organisation, and policy changes happening when there are no remaining 'paramount objections'.

The current hype about AI agents is another example; where startup kids in San Francisco are launching 10x agents in between popping peptides, the real impact of the LLMs-in-a-loop will be to trash whatever service they touch. It's not that AI agents will multiply our power but that their unreliability reflects the broader point of AI, which is to strip us of agency altogether.

We need reclaim agency through assemblies and workers' and people's councils as a basis for collective agency and counter power. On that note, I'd like to quote one of the organisers of the resistance to ICE in Minneapolis:

"In the first days of December, as it became clear that the ICE invasion was a real thing that was really happening to us, as groups of us gathered swapping rumors about the kidnappings and clearly inadequate tips about phone security, we had no idea what to expect, no idea what would happen, no idea what we were going to do. Only one thing was crystal clear: nobody, absolutely nobody, was coming to save us. It was clarifying. We knew, with complete certainty, that... if we don’t stand in their way when they come to kidnap our neighbors, nobody will stand in their way. If we don’t try to feed people who can’t work, can’t even go outside to get food, nobody will feed them. It put things into focus really fast."

We need to learn from systems that support self-organisation under emergency conditions, whether it's resistance to ICE or hurricane recovery, as ways to survive what's coming as well as to prefigure alternative futures.

The time is ripe for experiments in infrastructured mutuality, and if we want to start figuring out an anti-fascist approach to tech we should start with all the people who are being marginalised by the current approach. The disability movement, for example, has a ton to teach the rest of us about adapting tech for survivability in a world that is designed to be hostile to your very existence. As I said in the opening plenary, we need programme of decomputing as an anti-fascist approach to infrastructuring the common good.

Preprint: AI, Decomputing and the Interregnum

2026-03-08T00:00:00+00:00

new preprint: 'AI, Decomputing and the Interregnum'

cite as: McQuillan, D. (2026). AI, Decomputing and the Interregnum. Zenodo. https://doi.org/10.5281/zenodo.18908529

abstract:

This paper treats AI as diagnostic for the deeper changes taking place in the existing order of things. It uses AI's alignment with both the political economy and with the dualisms that underpin it, including race, gender and anthropocentrism, to highlight the nihilistic character of the current restructuring. AI's scaling and accelerationism are taken as examples of the wider tactics being invoked by hegemonic power to maintain control under changing conditions. From this perspective, the massive build-out of data centres isn't simply a seizure of energy resources but a manifestation of an aggressive and misogynist technopolitics. The paper argues that a liberal push for digital sovereignty doesn't interrupt these dynamics but plays into the hands of emerging technofascism. It proposes instead the prefigurative tactic of 'decomputing', which draws on degrowth, deautomatisation and a convivial approach to technology. It explores decomputing as a means to mitigate both material and relational harms and as a decisive turn towards infrastructuring the common good. The paper concludes that AI is the contradiction that reveals many others, not least the gap between claims to legitimacy and the actuality of destructive violence, and proposes an alternative technopolitics of reciprocity that prioritises care and sustainability.

AI is a morbid symptom of the interregnum

2026-02-19T00:00:00+00:00

This is the abstract for my Rogers Chair Public Lecture for Western University on 20th March 2026 at 5pm GMT, hosted by the Starling Centre for Just Technologies and Just Societies. URL for the talk tbc.

Let us begin from the contradiction that is AI. What does it mean that a technology which is functionally incapable of delivering on its claims continues to be the site of massive financial and strategic investment? This question can be fruitfully answered by treating AI as a diagnostic whose failings shed a light on underlying structural transformations. AI is a fake solution to real crises, especially the breakdown of the neoliberal world order and the unsettling of patriarchal subjectivity. Like all solutionism, it actually amplifies the very problems it’s intended to solve. The particular pathologies of AI, especially scaling and accelerationism, are symptoms of the actual restructuring taking place in relation to energy politics and increasing authoritarianism.

As a technopolitics of the interregnum, AI is a stark warning about the way hegemonic power intends to maintain control under changing conditions. It is also, therefore, a heuristic for possible alternatives. A movement of decomputing is one that tackles technology as the convergence of politics and subjectivity, as as raising the question of what kind of society we want to live in and who we need to be in order to inhabit that society. The antidote it proposes to the existing state of things involves degrowth, deautomatisation and a convivial approach to tool development that centres interdependence and situatedness. When tackling the rapacious energy and cooling demands of data centres, for example, decomputing turns the question to one of the re-socialisation of all of society’s energy and water resources. Decomputing calls for an infrastructural intersectionality that prefigures the material commons and the condition of care without categorisations.

Resisting GenAI & Big Tech in Higher Education

2025-11-25T00:00:00+00:00

My speaker notes & slides for the panel on 'Resisting GenAI & Big Tech in Higher Education', an event co-organised with the Climate Justice Universities Union (CJUU).

The panel: Christoph Becker (U of Toronto, CA), Mary Finley-Brook (U of Richmond, USA), Dan McQuillan (Goldsmiths U of London, UK), Sinéad Sheehan (University of Galway, Ireland) Jennie Stephens (National University of Ireland Maynooth, IE), and Paul Lachapelle (U of Montana, USA). Chair: Amy Woodson-Boulton (Loyola Marymount U, USA).

powerful forces but not a powerful technology

AI computations are correlations not causal relations, so its outputs are plausible rather than factual. It's a bullshit engine.
When it comes to AI, we're dealing with powerful forces but not with a powerful tech. AI is basically crap and investment in it is a bubble.
Large Language Models are sold to universities as learning accelerators but substitute slop for critical thinking.
Efforts to make AI more reliable actually make it more effective at selecting preferred, and usually "non-woke", versions of truth.
AI is precaritising rather than productive; it can't substitute for meaningful activity but it can make people's conditions more vulnerable.
So AI is extending forms of austerity prevalent since the crash of 2008 while preparing a new financial back hole all of its own.
AI isn't the future but its preemptive predictions and nihilistic dependencies foreclose futures for all of us.

leaderboard

The AI industry is always boasting about new models and improved metrics: "SOTA benchmarks across the board!"
But what does a leaderboard of AI metrics really represent?
Research suggests the effect of relying on generative AI is to make cognition 'atrophied and unprepared'.
The data centre energy consumption needed to deliver these numbers is measured in gigawatts.
The unchallenged inevitability of AI means that cloud companies can abandon their pretence at sustainability
It re-legitimises burning as much energy as possible, in the name of progress with a capital 'P'.
And AI isn't just growth-oriented, it's accelerationist; a far right pitch for power via intensified technological change.

total mobilisation

I think this convergence of ideology and infrastructure is what ultra-nationalist writer Ernst Jünger called ‘total mobilisation’.
Meaning "the conversion of life itself into energy" as nations are “driven relentlessly to seize matter, movement and force through the formalism of technoscience”.
This legitimates a new form of political order based on the vitalism of conflict.
And indeed, Big Tech has recently abandoned any commitments to the peaceful use of AI for the good of humanity blah blah.
Instead, it's rallying around renewed visions of national dominance through economic and especially military might.
But AI triumphalism is actually a diagram of underlying failure.
The neoliberal order is breaking down under its own contradictions and system shocks.
It has no answers to offer except sci-fi tech and increasing authoritarianism.

decomputing

I suggest we situate our resistance to AI inside and outside higher education as forms of decomputing.
Decomputing rejects scale because that drives carbon emissions,
but also because our agency is undermined by our immersion in a system of machinic relations, which includes the contemporary university
Decomputing is based on the principles of degrowth, care and conviviality.
We need systems that don't depend on continuous expansion, whether that's AI, universities or entire economies.
We need to start from care to counter algorithmic detachment and eugenicist abstractions.
Conviviality gives us ways to collectively assess tech's effects on relatedness and bio-interaction.
Wherever AI is proposed as ‘the answer’ there's already a structural problem.
One that's best addressed through the direct social relations of those most affected.

organising

Decomputing is a prefigurative technopolitics,
which tries to enact changed relations in the here-and-now.
One organisational form for this is worker's and people's councils on AI.
These are self-constituting assemblies that push back against AI bullshit,
while using consensus and critical pedagogy to tackle the divisive binaries we've all been programmed with.
Because universities are on the AI frontline, we're seeing resistance popping up all over the place.
Solidarity is the first priority of any of these critical collectives.
Some of the questions facing this emerging movement more broadly are:
how to move beyond reformism with minimum wasted energy and burn-out
how to coordinate and develop strategies without imposing rigid structure
how to position the push against AI as part of a movement-of-movements,
as part of an ecology of infrastructural intersectionalities.
AI isn't inevitable, but there's no going back because the past was already built on injustice; what we need to work towards are livable futures worth fighting for.

Opening Statement to the Irish Parliament Committee on AI

2025-11-18T00:00:00+00:00

My opening statement to the Irish Parliament (Oireachtas) joint Committee on Artificial Intelligence. The theme of the session was 'AI, Truth and Democracy'

I would like to thank the Committee for the invitation to participate in this discussion about AI, Truth and Democracy.

AI

AI is both a set of technologies, such as neural networks and transformer models, and a range of rhetorical claims. The technology and the claims are only loosely connected.
I will argue that AI undermines the ideals of truth and democracy.

Truth

AI has an adversarial relation with truth. The core of AI's calculations are correlations not causal relations, so it's outputs are plausible rather than factual.
AI's pattern recognition is, therefore, a form of computational conspiracy theory, and its outputs are disinformation even when they appear to be accurate.
AI's internal opacity and its inability to parse social complexity make it impossible to remove bias and errors.
While a belief in AI's superior powers persists, its claims to truth will retain authority while harming the most marginalised.
Even the engineers who build AI can't explain what's going on inside, so reliable regulation is a non-starter.
At the same time, the efforts to make AI more reliable actually make it more effective at selecting preferred, and usually "non-woke", versions of truth.
The claims that AI will solve everything from climate change to infectious disease deflect attention from the uncomfortable truths of our current moment.
This hubris is driving an investment bubble that diverts vast sums from real social needs.

Democracy

It's increasingly clear that AI is precaritising rather than productive; it can't replace people but it makes their conditions more vulnerable.
AI is extending forms of austerity prevalent since the crash of 2008 while preparing a new financial crash of its own, creating conditions which are corrosive to democracy.
In addition, AI is anti-democratic in terms of institutional and regulatory capture.
We are currently witnessing the EU walking back the flagship AI Act in the face of pressure from Trump and Big Tech.
Peter Thiel, founder of Palantir and patron of J. D. Vance, is on a lecture tour saying attempts to regulate AI are the work of the Antichrist.
Meanwhile, the example of DOGE demonstrated AI's effectiveness as a form of authoritarian cyberattack on centralised institutions.
More broadly, AI is toxic to democracy via its impact on education and young people.
Large Language Models are sold as learning accelerators but substitute slop for critical thinking.
They are becoming the first port of call for everything from essays to relationship advice.
AI undermines the replenishment of a citizenry with the capacity for independent thought.
In its systemic effects, AI will fail to solve problems, cause collateral damage, and will benefit reactionary politics.

Recommendations

I suggest that the committee avoid misleading responses to this state of affairs, such as the idea of AI sovereignty. AI should be considered harmful to whatever polity is hosting it.
The committee should at least be clear with itself what it's endorsing when it endorses AI. At best, the alleged benefits to healthcare and so on really amount to algorithmic Thatcherism. A more likely outcome is that widespread AI adoption will strengthen the far right.
I urge the committee to see AI as a symptom rather than a cause, and to use it as a diagnostic for the underlying problems of a system that needs restructuring for the benefit of people and planet.
Having said that, AI is an actor in its own right and one that will intensify real world problems like energy costs, unemployment and militarisation.
Therefore, I also encourage the committee to place worker and community collectives at the heart of decision-making about AI, with a clear power of veto.
This should also apply to expanding the number and/or scale of energy-hungry and recolonising data centres.
Decision-making around AI should prioritise alternative solutions that reduce the overall dependence on computation and elevate direct social relationships.

Not the digital transformation you planned for: AI accelerationism versus decomputing

2025-11-06T00:00:00+00:00

An abstract for the European University of Technology's (EUt+) webinar series on digital transformation.

REGISTRATION FORM

The EU's dubious vision of economic growth that could be digitally decoupled from carbon emissions has resulted in a deeply reactionary technopolitics. While it was never really the case that innovative tech efficiencies would magic up unlimited growth without climate consequences, the mask has really slipped with the advent of AI.

Massive institutional and financial buy-in is failing to conceal AI's character as an already-broken technology trying to fix a broken system. While AI's imaginaries are far-right-friendly and accelerationist, the material consequences include a re-centring of high energy consumption as a sign of progress.

This talk will propose decomputing as an alternative form of digital transformation; one that centres social justice, aligns with degrowth and applies people-powered conviviality to the governance of tech for the common good.

Low Carbon Computing versus The Blackpilled Anthropocene

2025-10-15T00:00:00+01:00

A talk for the Low Carbon and Sustainable Computing (LOCOS) seminar series at the University of Glasgow.

The video of the talk.

This talk will attempt to extend the idea of low carbon computing by calling for collective decision-making around the development and deployment of computational technologies. While progress can be made on both energy demands and embodied carbon, these are currently swamped by the accelerationist effects of technologies such as AI. Not only is our current political-economy unsustainable, as the IPCC points out, but the attempt to fix it through a fusion of AI and increased authoritarianism are only making things worse.

The talk will propose the concept of ‘decomputing’ as a response to the underlying dynamics of the blackpilled Anthropocene. Decomputing positions computing as first and foremost a matter of care; that is, as a practice that should pay attention to impact of technology on human and non-human relations. It draws on degrowth and deautomisation as ways to repair our environmental and democratic deficits, and proposes tools such as the Matrix of Convivial Technology (MCT) as means by which to transform the role of computation in society. While warning of the dangers latent in concepts like abstraction and efficiency, this talk will highlight the links between low carbon computing and the construction of alternative and more hopeful futures.

Decomputing as Resistance

2025-07-16T00:00:00+01:00

This is the text of a talk given as part of the lecture series “Unstitching Datafication”, organised by the Media for Cooperation research centre at the University of Siegen. It's very much a work-in-progress, and I'm interested in any comments or feedback: feel free to email me at resistingai@gmail.com or find me on social media.

intro

I would like to thank Christoph and the Media of Cooperation research centre for inviting me to be part of the Unstitching Datafication series. I'll try to honour the series by using terms like 'seams' and 'unstitching' in my talk.

This talk is titled 'Decomputing as Resistance'. In it, I will argue that contemporary AI reveals the seams our current system in ways that can't be ignored but have to be countered. Anyone who's used a large language model for any amount of time will be familiar with how glitch-prone they are. I'm proposing that AI is itself a glitch; a stuttering misstep of the neoliberal order that hints at nothing less than internal disarray.

What I'll be proposing as a countermeasure is decomputing; an approach that takes direct aim at AI, but is concerned with unstitching more than just the digital. Decomputing is a way of reconfiguring our broader social and economic relations.

ai considered harmful

When I talk about AI I'm referring to the specific technologies that legitimate so much social and environmental damage right now, which are neural networks and transformer models.

It's been fascinating to watch the rise of these mechanisms of AI, because they're always faking it. Predictive AI is as unreliable as generative AI; they're both giant operations in pattern-matching whose only hold on reality is correlation. It's QAnon as computer science.

The fact that they're also foundationally opaque makes it impossible to meaningfully disentangle the internal process that led to a particular output. Pro-tip: reasoning models can't really tell you how they got to an answer. And yet, AI is presented as the generalisable solution to society's trickiest problems, and an agent that's so intelligent it will definitely be able to replace you.

While actual AI isn't fit to replace anything or anyone, it does work as an engine of precaritisation and marginalisation, of Uber and algorithmic welfare cuts, It's an apparatus that crudely extracts as much encoded human knowledge as it can in order to provide a shoddy substitute for key social functions like education and healthcare, while further concentrating wealth and power.

infrastructural violence

This structural violence is now complemented by equally egregious amounts of environmental violence.

As we now realise, the alleged benefits of a chatbot in your pocket come with a shockingly high price in terms of energy use and water consumption, and a GPU supply chain that depends on colonial extractivism and conflict minerals.

It's not so much that AI's energy demands are the leviathan that tips us over into irreversible climate change; the fossil fuel industry and industrial farming don't need any help on that front.

It's more that the unchallenged inevitability of AI as the only future for economic development and the key to geopolitical power means that AI companies can abandon their performative pretence at sustainability, and become instead a way to re-legitimise burning as much energy as possible.

It means that when decaying national infrastructures that already stagger under the burden of privatised profiteering are brought to moments of collapse by the additional demands of datacentres, the AI will get priority over mere human needs.

scale

I want to focus for a moment on scale as the concept that binds together the technical and social apparatus of AI.

The connectionist model of AI that underpins it all has existed for decades, but was largely ignored up to 2012 because it took too much data and computing power to grind out plausible answers. The unfortunate convergence of social media, crowdsourced datasets and GPUs changed all that.

The AI industry has since generated a mini-universe of self-reinforcing and eugenics-flavoured metrics that claim to measure progress while failing to tackle the things that really need to change. The basic driver of success on these metrics is the scaling of datasets and computing power. If we count computing as floating-point operations or FLOP we've gone from early AlexNet at 10^17 FLOP to recent models at 10^25 FLOP or more. To put that into perspective, this scaling outpaces any other so-called tech revolution from mobile phone adoption to genome sequencing.

The overarching logic of all industry metrics is exactly the same as GDP; the only thing that matters is growth, growth, growth, no matter the collateral damage along the way. Unrestricted scaling is a vision of infinite growth based on identifying previously unrealised forms of enclosure, and also a claim to forms of knowledge that will reach beyond human understanding.

It's scale that attracts the impatient flows of venture capital, and scale that underpins claims about emergent superintelligence. In the eyes of AI's advocates there are no social, environmental or planetary limits. Indeed, they argue for going further and faster because only AI can save us from the climate crisis and cure all human disease.

total mobilisation

I suggest that the convergence of forces around AI infrastructure can be understood as a form of ‘total mobilisation’, a term coined in the 1930s by ultra-nationalist writer Ernst Jünger to characterise the channelling of the entire material and energy resources of a nation into a new technological order.

His claim was that we have entered a new era, one that requires "the conversion of life itself into energy" as nations are “driven relentlessly to seize matter, movement and force through the formalism of technoscience”

Total mobilisation legitimates a new form of political order based on the vitalism of conflict. In the present moment, we're seeing the big AI companies abandon their stated commitments to the common good and rally round renewed visions of national dominance through military and economic might.

The outcome of mobilising all available energies isn't simply capital accumulation but the severing of society from its previous moorings, and an alignment with Jünger's vision of a breakthrough to a new epoch through violent technological transformation.

Reading the incessant push for more and more AI through the lens of total mobilisation makes sense of its apparent nihilism as a Nietzschean will to power.

technofascism

I'm not saying that our tech and political leaders are keen students of Jünger's ideas. It's more that total mobilisation captures the cult-like levels of commitment to AI from corporate bosses and national governments alike.

The neoliberal order is breaking down under the accumulated weight of its own contradictions and the resulting system shocks, like austerity and climate change. Those who wish to maintain a massive asymmetry of power and wealth seem to have no answers aside from claims about sci-fi technology and increasing authoritarianism.

Total mobilisation resonates strongly with the accelerationism and politics of neoreaction that deeply pervade the tech industry and form the bridge to political movements like MAGA and the far right. Understanding these developments alongside the proliferation of AI infrastructure as a form of total mobilisation suggests that we're dealing with a technopolitical phase shift, one that won't be dissuaded or held back by rationality or regulation and will treat those lives outside the tiny elite destined to lead this change as essentially disposable.

degrowth

Decomputing is an attempt to respond to the ever-growing social and environmental damage resulting from our current direction of travel. Decomputing identifies a rejection of scale as a way to mitigate the worst effects and a heuristic for alternative ways forward.

AI's scaling has appeal and power because it arises within a broader system based on the unifying principle of unconstrained growth. Decomputing is a turn towards degrowth, as a direct challenge to AI's extractivism and to the systemic logics underpinning it.

Most importantly, degrowth isn't merely a refusal to depend on expansionism but a switch of focus to an alternative metabolism based on sustainability and social justice. Decomputing seeks to interrupt AI's extractivism in the here and now in ways that align with a transformation of the wider political economy.

deautomatisation

Decomputing also opposes scale because it induces automatisation; that is, a state where autonomy and the capacity for critical thought are undermined by immersion in a system of machinic relations.

In this sense, AI is an intensification of the institutional, bureaucratic and market structures which already strip agency from workers and communities and place it instead in opaque and abstract mechanisms. Decomputing, by contrast, is the disentangling of thought and relations from AI's reductive influences.

As a practical example, decomputing would challenge the way the threat of algorithmic welfare cuts is justified by having a human-in-the-loop, as if this guaranteed due process and as if no-one had ever heard of automation bias or choice architecture. Decomputing is the process of developing alternative forms of organisation and decision-making that draw instead on reflective judgement and situated responsibility.

Decomputing is therefore as much about deprogramming society from its technogenic certainties as it is about decarbonising its computational infrastructures.

Datafication and an ideology of efficiency play into AI's careless and dehumanising optimisations. Decomputing attempts to wrest social praxis away from the utilitarian cruelty that is openly celebrated by the adherents of reactionary technopolitics. It is a deliberate turn away from the alienating frameworks of efficiency and optimisation and a return to context and ‘matters of care’ where our mutual vulnerabilities and dependencies are central to social reproduction.

convivial tools

Decomputing asserts that the development and deployment of any advanced technologies should be subject to social sanction. While uncommon now, it was widely argued in the 1970s and 1980s that the adoption of technology likely to have a widespread impact on society should depend on critical interrogation and collective approval.

We can lift directly from those tendencies in the form of Illich's work on tools for conviviality. He defined tools as both technologies and institutions, and convivial tools as those that enabled the exercise of autonomy and creativity, rather than the conditioned responses demanded by manipulative systems.

The Matrix of Convivial Technologies extends Illich’s ideas by specifying questions through which conviviality can be assessed, including accessibility (who can build or use it?), relatedness (how does it affect relations between people?) and bio-interaction (how does the tech interact with living organisms and ecologies?).

people's councils

However, it's unlikely that we're going to get very far by simply asking reasonable questions about the point of all this mobilisation. The power of big tech has extended beyond regulatory capture to a level of state capture, or at least, to a situation where there's an increasing merger with political structures.

Our current systems are incredibly fragile. DOGE did a good job of showing the seams, when it demonstrated that the centralisation and digitisation of institutions renders them vulnerable to what was essentially a form of far right cyberattack.

Decomputing takes instead a prefigurative approach to technopolitics, in that its practice enacts the forms of empowerment and sustainable relations that it seeks to bring about. The basic form of decomputing is the kind of assembly that I've described elsewhere as workers' and people's councils.

This kind of collectivity, self-constituting and rooted in local context and lived experience, can be applied at any level and in any setting, from parent-teacher associations who object to young minds being made dependent on chatbots to communities threatened by the construction of a hyperscale datacentre.

Wherever AI is proposed as 'the answer', is already a seam that needs unstitching, a structural problem where those who are directly involved should be at the forefront of determining what needs to be changed instead.

technopolitical resistance

Resistance to datacentres, which we can already see happening from the Netherlands to Chile shows the potential of intersecting seams, or what I would call infrastructural intersectionality. These intersections occur because the same communities who experience power cuts due to local grid overload or breath polluted air from gas turbines, like the black communities living around Musk's XAI datacentre in Memphis, are also likely to work in exploitative jobs where their immediate boss is basically an algorithm.

It's not hard to imagine a situation where resistance to a new datacentre is in solidarity with the wildcat strikes of workers in the local Amazon fulfillment centre through a joint assembly of workers and the community.

I think we can see a different dimension of the potential for decomputing in the disability movement. They are resisting savage cuts to welfare justified by stigmatising algorithms of suspicion, and through being labelled as unproductive members of society. They also have a deep understanding of the way disability itself is socially constructed by the technologies that society chooses to use or not to use.

The concept of crip technoscience is a critique of this role of tech, combined with approaches to hacking and adapting it to make people's lives more livable; hence creating convivial technologies that are sustainable and enabling.

decomputing

Decomputing is the development of a counter-power to the technopolitical apparatus of AI and its totalising transformations.

What decomputing proposes is one pathway towards societies built on relations of care, whose attributes aren’t abstraction and manipulation but mutual aid and solidarity. It asserts that that autonomy, agency and collective self-determination are in inverse proportion to the degree to which human relations are skewed by algorithmic ordering.

Decomputing is the prefigurative decoupling of advanced computation from social goals. It's the reassertion of the need for convivial tools and the construction of forms of collective social power that can bring them into being.

There are examples of contemporary struggles that don't start directly from resisting AI, but nevertheless combine the practice of self-organised resistance with the goal of constructing alternative futures. One such example is the GKN factory collective, where a factory in Italy making vehicle axles was bought by a hedge fund that tried to close it down and cash out. The workers refused, occupied their workplace and formed a collective with the local community to repurpose their tools for a just transition; that is, for worker justice and environmental sustainability. They now produce cargo bikes and recycle solar panels and are continuing their struggle under the partisan slogan 'Insorgiamo!' or 'We Rise Up!'.

a world to win

Demanding the social determination of technology is a way to unstitch the loss of collective agency which has resulted from decades of neoliberalism.

It's this collective agency that we're going to need to resist the rising wave of fascist political movements that want to roll back every kind of social equality, and project their nihilistic vision through technologies that are already coded as anti-worker and anti-democratic.

And this is my final point about decomputing, that it's not a vision for any return to a pre-AI status quo but a deliberate claim on a better world for all. Effective resistance has never been founded on a defence of an already unjust state of affairs. It only makes sense as the precursor to something better, by having the goal of a fairer and more solidaristic society.

Decomputing is the combination of degrowth and critical technopolitics that says other worlds are still possible, and that we intend to bring them into being.

Resisting the Techno-Fascist Takeover: Are We Ready for Decomputing?

2025-06-26T00:00:00+01:00

I have a new piece out in the Berliner Gazette: 'Resisting the Techno-Fascist Takeover: Are We Ready for Decomputing?